JP2015049697A - Information processing apparatus, information processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enable appropriate management and search of information.SOLUTION: An information processing apparatus according to one embodiment of the present disclosure includes a collection unit, a storage unit, and a search unit. The collection unit collects a plurality of first metadata relating to information for which a common specification to a plurality of information sources transmitting the information is not stipulated, from the information sources. The storage unit stores a first attribute indicating an item of an element included in the first metadata and a first attribute value that is a value corresponding to the first attribute while making the first attribute and the first attribute value correspond to each first metadata. The search unit searches the plurality of first metadata on the basis of a correspondence between a second attribute indicating an item of an element included in newly acquired second metadata and a second attribute value corresponding to the second attribute and the first attribute and the first attribute value, and extracts corresponding metadata that is the first metadata corresponding to the second metadata.

Description

  Embodiments described herein relate generally to an information processing apparatus, a method, and a program.

  There is a need for a system that collects information from government agencies, local governments, and citizens over a wide area and monitors the situation. For example, in the event of a disaster, collecting information from a plurality of information sources and centrally managing the safety information of citizens is also useful in terms of information reliability. As such a system, there is a method of unifying and managing geospatial information and information to be managed.

JP 2012-194620 A

  However, in the above method, in order to integrate and manage a plurality of regional information and disaster prevention information with different jurisdictions, standardization for unifying data is essential, and the information to be managed is geographical Association with spatial information is essential. Therefore, the information sources from which data can be collected are limited, and for example, the situation of areas outside the jurisdiction of the local government cannot be grasped.

  The present invention has been made to solve the above-described problem, and an object thereof is to provide an information processing apparatus, method, and program capable of appropriately managing and searching information from a plurality of information sources. To do.

  An information processing apparatus according to an embodiment of the present invention includes a collection unit, a storage unit, and a search unit. The collection unit collects first metadata relating to information that does not have a common standard among the plurality of information sources, from a plurality of information sources that transmit information. The storage unit stores a first attribute indicating an item of an element included in the first metadata and a first attribute value that is a value corresponding to the first attribute in association with each first metadata. . The search unit associates the second attribute indicating the item of the element included in the newly acquired second metadata and the second attribute value corresponding to the second attribute with the first attribute and the first attribute value. A plurality of the first metadata is searched based on the relationship, and corresponding metadata that is the first metadata corresponding to the second metadata is extracted.

1 is a block diagram showing an information processing system including an information processing apparatus according to a first embodiment. The figure which shows an example of the metadata stored in a metadata storage part. 5 is a flowchart showing search processing of a metadata search unit according to the first embodiment. The flowchart which shows the search process of the metadata search part which concerns on the modification of 1st Embodiment. The figure which shows an example in the case of matching with the missing attribute value. The block diagram which shows the information processing system containing the information processing apparatus which concerns on 2nd Embodiment. The flowchart which shows the search process of the metadata search part which concerns on 2nd Embodiment. The figure which shows the specific example of the search process of the metadata search part which concerns on 2nd Embodiment. The block diagram which shows the information processing system containing the information processing apparatus which concerns on 3rd Embodiment. The flowchart which shows the process of the metadata search part and importance calculation part which concern on 3rd Embodiment.

Hereinafter, an information processing apparatus, method, and program according to an embodiment of the present disclosure will be described in detail with reference to the drawings. In the following embodiments, the same numbered parts are assumed to perform the same operation, and repeated description is omitted.
(First embodiment)
An information processing system including an information processing apparatus according to the first embodiment will be described with reference to the block diagram of FIG. In the present embodiment, information collection at the time of a disaster is described as an example, but the present invention is not limited to this and can be applied to any event. For example, the present invention can be similarly applied to information such as a fireworks display planned by a local government, a lecture, a sale date of a commercial facility, and information on transportation such as a train operation state or a traffic jam on a road.

  The information processing system 100 according to the first embodiment includes information sources 151, 152, 153, 154 and 155, metadata generation units 161, 162, 163, 164 and 165, an information processing apparatus 101 and a thesaurus dictionary 106. The information processing apparatus 101 includes a metadata collection unit 102, a metadata storage unit 103, a metadata search unit 104, and a display unit 105.

The information source 151 is, for example, a fixed point camera installed in a commercial facility, a shelter, or a road, and generates a moving image by the camera.
The information source 152 is, for example, a microphone installed in a public facility or a shelter, and generates a user's voice signal when the user speaks into the microphone.
The information source 153 is, for example, a disaster announcement or official announcement from the local government and mass media, and generates text data such as web from information transmitted from the local government or the media. Note that an audio signal may be generated for an audio presentation such as an official conference.

The information source 154 is, for example, a weather sensor, and generates information on weather such as temperature, humidity, and wind speed as numerical values.
The information source 155 is, for example, a general citizen (also referred to as a general user) who uses an SNS (social networking service), and generates text data such as disaster information posted by the general user using the SNS. In addition, when a general user transmits information by a moving image, a sound, or the like, a moving image and a sound signal may be acquired, respectively.

  The metadata generation unit 161 receives a camera image (still image or moving image) from the information source 151, and an identifier (ID) of the camera that acquired the camera image, date / time information about the date and time when the camera image was acquired, and a camera are installed. Metadata including position information regarding the position is generated and associated with the camera image. Further, by using object recognition technology, a person reflected in a camera image, an object such as a building or a car, a disaster such as fire or smoke may be recognized, and the name of the recognized object may be included in the metadata. Furthermore, the face image of the recognized person may be collated with a registered profile image using a service in which the face image is registered such as SNS, and the first and last name of the person may be included in the metadata. In addition, the text may be extracted by recognizing the character image shown in the camera image using the OCR technology and included in the metadata.

  The metadata generation unit 162 receives an audio signal from the information source 152, and includes an identifier (ID) of the microphone that acquired the audio signal, date and time information about the date and time when the audio signal was acquired, and position information about the position where the microphone is installed. Generate data and associate it with audio signals. Further, a speech signal may be converted into text and included in the metadata by using speech recognition technology. Furthermore, natural language processing technology may be used to extract specific expressions such as person names and place names from the text and include them in the metadata.

  The metadata generation unit 163 receives the text data from the information source 153, and obtains the identifier (ID) of the local government or the media that announced the text data, the date and time information regarding the date and time when the text data was announced, and the location information about the local government and the location of the media. Generate metadata to include and associate with text data. Also, natural language processing technology may be used to extract specific expressions such as person names and place names from text data and include them in the metadata.

The metadata generation unit 164 receives a numerical value observed for the observation target from the information source 154, an identifier (ID) indicating the observation target, date / time information regarding the date and time when the numerical value was acquired, and a position indicating which area the information is related to Generate metadata including information and associate it with numerical values.
The metadata generation unit 165 receives text data from the information source 155, generates metadata including date and time information regarding the ID of the user who created the text data and the date and time when the text data was created, and associates the text data. Also, natural language processing technology may be used to extract specific expressions such as person names and place names from text data and include them in the metadata. Furthermore, paying attention to the part of speech of the word included in the text data, the intention of the user who created the text data, for example, “I want to know” or “I want it”, “Where is the refuge?” “Is the train moving?” May be determined and included in the metadata. It is desirable that the position information when the text data is generated in the information source 155 is not necessarily required from the viewpoint of protecting the privacy of general users.

  Note that the information sources 151, 152, 153, 154, and 155 may include metadata generation units 161, 162, 163, 164, and 165, respectively. The processing of the metadata generation unit uses general processing. Is feasible.

  The metadata collection unit 102 collects metadata from the metadata generation units 161, 162, 163, 164, and 165, respectively. The interval for collecting the metadata may be collected at regular time intervals, or may be collected every time new metadata is generated from the information source. Note that when collecting metadata, moving images, audio signals, numerical values, and text data corresponding to the metadata may also be collected.

The metadata storage unit 103 receives and stores metadata from the metadata collection unit 102. When the metadata collection unit 102 collects each moving image, audio signal, numerical value, and text data corresponding to the metadata in the metadata collection unit 102, the metadata storage unit 103 may store them together with the metadata. Further, each moving image, audio signal, numerical value, and text data may be stored in an external storage unit (not shown) and associated with metadata stored in the metadata storage unit 103.
The metadata search unit 104 searches the metadata stored in the metadata storage unit 103 for the metadata that is newly stored, searches for the corresponding metadata, and extracts the corresponding metadata as the corresponding metadata. The metadata search process may be performed at regular time intervals or each time metadata is newly stored. A specific example of the search process of the metadata search unit 104 will be described later.

The display unit 105 receives the corresponding metadata from the metadata search unit 104, and displays the searched corresponding metadata on the display, for example.
The thesaurus dictionary 106 stores synonyms and synonyms, and presents synonyms and synonyms in response to a request from the metadata search unit 104.

Next, an example of metadata stored in the metadata storage unit 103 will be described with reference to FIG. In FIG. 2, metadata generated from a moving image captured by a commercial facility camera will be described as an example.
The metadata 200 includes an attribute 201 and an attribute value 202, is associated with each other, and is stored in the metadata storage unit 103 for each metadata. An attribute 201 is a metadata item name, and an attribute value 202 is a value or state corresponding to the attribute 201. In the example of FIG. 2, the attribute 201 includes an account ID 203, position information 204, date / time information 205, an event 206, and a situation 207.

The account ID 203 is an identifier indicating an account in an affiliation facility or an SNS. Here, the ID of the camera in the facility, the attribute 201 “account ID” and the attribute value 202 “commercial facility A_camera 1” are associated with each other.
The position information 204 is the position information of the information source and the position information of the person or facility that is the center of the topic transmitted from the information source. Here, the position information 204 is information regarding the position where the camera 1 is installed. The position information may be information regarding latitude and longitude.
The date / time information 205 is the date / time when the information is acquired. Here, the date / time captured by the camera is stored as the attribute value 202.
Event 206 indicates what event is occurring.
The situation 207 indicates what the situation of the event 206 is.

Next, search processing of the metadata search unit 104 according to the first embodiment will be described with reference to the flowchart of FIG.
In step S301, metadata newly stored in the metadata storage unit 103 is read.
In step S <b> 302, date / time information is specified from the attributes and attribute values included in the metadata, and metadata having an attribute value included in a predetermined period as the date / time information is searched from the metadata storage unit 103.
In step S303, position information is specified from attributes and attribute values included in the metadata, and metadata having an attribute value included in a predetermined area as position information is searched from the metadata storage unit 103.

  In step S304, it is determined whether corresponding metadata exists based on step S302 and step S303. If the corresponding metadata exists, the process proceeds to step S305. If the corresponding metadata does not exist, the process returns to step S301, and the same processing is repeated.

In step S305, metadata corresponding to the attribute of the newly stored metadata is identified from the corresponding metadata, and the similarity of the corresponding attribute value is calculated.
When metadata is generated for each information source that does not have a common standard with each other, the item name listed as the attribute 201 may be different for each information source. Here, the “common standard” defines the name of an attribute included in metadata and the type and range of values that can be taken as attribute values. Assume that the format for expressing metadata is unified. Examples of such data formats include CSV (Comma Separated Value, comma separated text data), JSON (Java (registered trademark) Script Object Notation), Linked Dat, and the like. In such a case, it is only necessary to extract metadata whose attribute value similarity is equal to or greater than a threshold value. The determination as to whether the degree of similarity is equal to or greater than a threshold value may be made by, for example, calculating the edit distance and cosine similarity of the character string representing each attribute value, or determining a synonym using a thesaurus dictionary.

  In step S306, among the corresponding metadata, metadata whose attribute value matches the attribute value of the newly stored metadata is specified, the similarity of the corresponding attribute is calculated, and the similarity is equal to or greater than the threshold value. Extract metadata. Specifically, for example, if “date and time”, “date information”, “Time”, and the like are attributes, they are synonyms representing time, and therefore the similarity of these attributes can be determined to be equal to or greater than a threshold value.

  In step S307, the extracted metadata is output as corresponding metadata. Thus, the search process of the metadata search unit 104 ends. Note that only one of step S305 and step S306 may be processed to determine the similarity of attributes or attribute values.

A specific example of similarity determination will be described with reference to FIG. 2 described above.
In FIG. 2, when the attribute 201 of the metadata 200 and the attribute 201 of the metadata 210 are compared, the position information 204 and the date / time information 205 match, but the event 206 and the disaster do not match. . In this case, if the attribute 202 “fire” of the event 206 matches the attribute value 202 “fire” of the disaster, and the similarity between the event and the disaster can be determined to be equal to or greater than the threshold, the metadata 200 Data 210 can be extracted as corresponding metadata.

(Modification of the first embodiment)
Among the collected metadata, a part of attribute value is missing, that is, metadata that does not contain a value is assumed. Even in such a case, the corresponding metadata can be obtained by referring to the attribute and the attribute value.

  The operation of the metadata search unit 104 according to the modification of the first embodiment will be described with reference to the flowchart of FIG. Note that the processing from step S301 to step S307 is the same as that in FIG.

  In step S401, it is determined whether or not the attribute value of the newly stored metadata includes a defect. If the attribute value includes a defect, the process proceeds to step S402. If the attribute value does not include a defect, the process proceeds to step S404.

  In step S402, the newly stored metadata is compared with the corresponding metadata in step S304, and the attribute corresponding to the missing attribute value of the newly stored metadata is determined from the corresponding metadata in step S304. Extract.

  In step S403, the missing attribute value is associated with the metadata attribute value extracted in step S402.

  In step S404, it is determined whether or not a defect is included in the attribute value of the searched metadata. If the attribute value includes a defect, the process proceeds to step S405. If the attribute value does not include a defect, the process proceeds to step S305, and the same processing is repeated.

  In step S405, the searched metadata is compared with the newly stored metadata, and the attribute corresponding to the missing attribute value of the searched metadata is extracted from the newly stored metadata.

  In step S406, the missing attribute value is associated with the attribute value of the metadata extracted in step S405. This is the end of the operation of the metadata search unit 104 when the attribute value is used.

Next, a specific example of associating with a missing attribute value will be described with reference to FIG.
FIG. 5 assumes a case in which metadata 501, 502, and 503 are stored in the metadata storage unit 103 in this order, and the metadata 502 shows a case where some of the attribute values are missing. Note that the metadata 501 is metadata generated from the camera image of the fixed point camera, and the person “Taro Yamada” is recognized using the object recognition technology. This metadata is generated from transmission on the SNS, and the metadata 503 is generated by using a speech recognition technology or a natural language processing technology from text data uploaded to a speech signal or a web in a shelter. Assume metadata.

  Specifically, the attribute value 504 corresponding to the attribute “photo” in the metadata 502 and the attribute value 505 corresponding to the attribute “situation” are missing. That is, this metadata 502 is an example of metadata generated using natural language processing technology when Hanako Suzuki sends information such as “I want to know the situation of Taro Yamada”.

  When the correspondences are compared according to step S402 and step S403 in FIG. 4, the name “Taro Yamada” matches, and the image associated with the metadata 501 can be determined to be Taro Yamada. / 11 14:50 ", information on survival confirmation can be obtained.

  Subsequently, when the metadata 503 is newly stored, the correspondence is compared with the metadata 502 having a missing attribute value in accordance with steps S405 and S406. At this time, the name “Taro Yamada” matches and the missing attribute “situation” of the metadata 502 matches the attribute “situation” of the metadata 503, so that the attribute value “ “Survival confirmation” can be associated. As a result, information that Taro Yamada is alive can be extracted as new information. Thus, for example, when searching for a person, it is possible to accurately retrieve previous information and latest information about the person.

  According to the first embodiment described above, even when metadata that is not standardized is collected from a plurality of information sources, it is determined based on the similarity of attributes and attribute values included in the metadata. Information can be managed and searched properly. In addition, even when information is missing, information can be supplemented from other metadata, and necessary information can be searched from a wide variety of data, and more accurate information can be obtained.

(Second Embodiment)
The second embodiment is different in that metadata is searched with reference to an interest relationship (follow relationship) between a plurality of information sources.

An information processing system including an information processing apparatus according to the second embodiment will be described with reference to the block diagram of FIG.
An information processing system 600 according to the second embodiment includes information sources 151, 152, 153, 154 and 155, metadata generation units 161, 162, 163, 164 and 165, and an information processing device 601. The information processing apparatus 601 includes a metadata collection unit 102, a metadata storage unit 103, a display unit 105, a follow relationship storage unit 602, and a metadata search unit 603.

  Other than the follow relationship storage unit 602 and the metadata search unit 603 are the same as those in the first embodiment, and a description thereof will be omitted here.

  The follow relationship storage unit 602 stores follow relationships of a plurality of information sources. The follow relationship may be, for example, an anthropomorphic of each of a plurality of information sources, each having an SNS ID, and storing the follow relationship in the SNS indicating whether or not they are interested in each other. Specifically, when a citizen is interested in a camera image of a commercial facility A (so-called LIVE camera or the like) or interested in sending information from a certain local government, a follow relationship can be established. Here, the follow relationship has a direction, and in this example, the follower is connected to the video of the camera of the commercial facility A, which is a non-follower, and the local government. The follow relationship storage unit 602 may refer to an external follow relationship database.

  The metadata search unit 603 is substantially the same as the metadata search unit 104, except that the corresponding metadata is searched with reference to the follow relationship stored in the follow relationship storage unit 602.

  Next, search processing of the metadata search unit 603 according to the second embodiment will be described with reference to the flowchart of FIG.

  Since the processing from step S301 to step S307 and from step S401 to step S406 is the same as that in the flowchart of FIG. 4, description thereof is omitted here.

  In step S701, the metadata of the account ID that follows the account ID of the newly stored metadata is referred to the follow relationship storage unit 602 for each follow relationship of the account ID among the extracted corresponding metadata. Extract with priority.

Next, a specific example of the corresponding metadata search processing using the follow relationship will be described with reference to FIG.
As shown in FIG. 8, in the follow relationship 801, an account ID 802 and a follow ID 803 are associated with each other. The account ID 802 is the same as the account ID included in the metadata. The follow ID 803 indicates an ID that follows the account ID 802. Here, the person name is a follow ID.

In the example of FIG. 8, a fire moving image is captured by the fixed point camera A of the commercial facility A, and metadata 804 is obtained. Ichiro Sato, a citizen, says on the SNS “Fire at Commercial Facility A” and gets metadata 805. In addition, it is assumed that Jiro Yamamoto also said “Smoke at commercial facility A” on SNS and obtained metadata 806.
At this time, referring to the follow relationship 801, Ichiro Sato follows the fixed point camera of the commercial facility A, and Jiro Yamamoto does not follow the fixed point camera of the commercial facility A. Jiro Yamamoto, who is following the fixed point camera at commercial facility A, is considered more interested in the fixed point camera at commercial facility A than Ichiro Sato, who is not following the fixed point camera at commercial facility A. Therefore, the speech of Ichiro Sato is considered to reflect the local situation rather than the speech of Jiro Yamamoto, so the metadata 805 is preferentially extracted as corresponding metadata.

  According to the second embodiment described above, it is possible to extract metadata of an information source with higher reliability by referring to the follow relationship.

(Third embodiment)
The third embodiment is different in that the importance of the corresponding metadata is determined with reference to the follow relationship.

An information processing system including an information processing apparatus according to the third embodiment will be described with reference to the block diagram of FIG.
An information processing system 900 according to the second embodiment includes information sources 151, 152, 153, 154 and 155, metadata generation units 161, 162, 163, 164 and 165, and an information processing device 901. The information processing apparatus 901 includes a metadata collection unit 102, a metadata storage unit 103, a display unit 105, a metadata search unit 104, a follow relationship storage unit 602, and an importance level calculation unit 902. Note that, as in the second embodiment, an external follow relationship may be referred to without including the follow relationship storage unit 602.
Except for the importance calculation unit 902, the process is the same as that of the first embodiment, and a description thereof will be omitted.

  The importance calculation unit 902 refers to the follow relationship stored in the follow relationship storage unit 602 and calculates the importance for each corresponding metadata.

Next, operations of the metadata search unit 104 and the importance calculation unit 902 according to the third embodiment will be described with reference to the flowchart of FIG.
The processing from step S301 to step S307, from step S401 to step S406, and step S701 is the same as that described above, so description thereof is omitted here.
In step S1001, the number of other account IDs that follow the metadata account ID is calculated for the metadata extracted in step S701, and the importance is determined. The importance may be set higher as the number of cases increases, or metadata that associates the age or region with each account ID is built, and weighted with those information May be set.
In step S1002, the corresponding metadata is output in descending order of importance. For example, it is only necessary to output the top three highest importance levels. It should be noted that all corresponding metadata to which importance is attached may be output.

  According to the third embodiment described above, metadata of an information source with high reliability can be extracted by calculating the importance based on the follow relationship.

The instructions shown in the processing procedure shown in the above-described embodiment can be executed based on a program that is software. The general-purpose computer system stores this program in advance and reads this program, so that the same effect as that obtained by the information processing apparatus described above can be obtained. The instructions described in the above-described embodiments are, as programs that can be executed by a computer, magnetic disks (flexible disks, hard disks, etc.), optical disks (CD-ROM, CD-R, CD-RW, DVD-ROM, DVD). ± R, DVD ± RW, Blu-ray (registered trademark) Disc, etc.), semiconductor memory, or a similar recording medium. As long as the recording medium is readable by the computer or the embedded system, the storage format may be any form. If the computer reads the program from the recording medium and causes the CPU to execute instructions described in the program based on the program, the same operation as the information processing apparatus of the above-described embodiment can be realized. Of course, when the computer acquires or reads the program, it may be acquired or read through a network.
In addition, the OS (operating system), database management software, MW (middleware) such as a network, etc. running on the computer based on the instructions of the program installed in the computer or embedded system from the recording medium implement this embodiment. A part of each process for performing may be executed.
Furthermore, the recording medium in the present embodiment is not limited to a medium independent of a computer or an embedded system, but also includes a recording medium in which a program transmitted via a LAN, the Internet, or the like is downloaded and stored or temporarily stored.
Further, the number of recording media is not limited to one, and when the processing in this embodiment is executed from a plurality of media, it is included in the recording medium in this embodiment, and the configuration of the media may be any configuration.

The computer or the embedded system in the present embodiment is for executing each process in the present embodiment based on a program stored in a recording medium. The computer or the embedded system includes a single device such as a personal computer or a microcomputer. The system may be any configuration such as a system connected to the network.
In addition, the computer in this embodiment is not limited to a personal computer, but includes an arithmetic processing device, a microcomputer, and the like included in an information processing device. ing.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

100, 600, 900 ... Information processing system, 101, 601, 901 ... Information processing apparatus, 102 ... Metadata collection unit, 103 ... Metadata storage unit, 104, 603 ... Metadata Retrieval part, 105 ... Display part, 106 ... Thesaurus dictionary, 151 to 155 ... Information source, 161 to 165 ... Metadata generation part, 200, 210, 501 to 503, 804 to 806 ... Metadata, 201 ... attribute, 202,504,505 ... attribute value, 203,802 ... account ID, 204 ... location information, 205 ... date / time information, 206 ... event, 207 ... Situation, 602 ... Follow relationship storage unit, 801 ... Follow relationship, 803 ... Follow ID, 902 ... Importance calculation unit.

Claims (10)

A collection unit that respectively collects first metadata related to the information that does not have a common standard among the plurality of information sources from a plurality of information sources that transmit information;
A storage unit that stores a first attribute indicating an item of an element included in the first metadata and a first attribute value that is a value corresponding to the first attribute in association with each first metadata;
Based on the correspondence between the second attribute indicating the item of the element included in the newly acquired second metadata, the second attribute value corresponding to the second attribute, and the first attribute and the first attribute value An information processing apparatus comprising: a search unit that searches a plurality of the first metadata and extracts corresponding metadata that is the first metadata corresponding to the second metadata. The first attribute includes an identifier of the information source, position information of the information source, and date information when the information source generated the information,
The search unit has at least either the similarity between the second attribute and the first attribute is greater than or equal to a threshold, or the similarity between the second attribute value and the first attribute value is greater than or equal to the threshold. The information processing apparatus according to claim 1, wherein the corresponding metadata is extracted based on one of them. The first attribute includes an identifier of the information source, position information of the information source, and date information when the information source generated the information,
The search unit extracts, as the corresponding metadata, first metadata including a first attribute and a first attribute value similar to the second attribute and the second attribute value by referring to a thesaurus dictionary. The information processing apparatus according to claim 1.   When at least a part of the second attribute value corresponding to the second attribute included in the second metadata is missing, the search unit has a similarity with the second attribute equal to or greater than a threshold value. When the first metadata having one attribute is extracted as the corresponding metadata, and at least part of the first attribute value corresponding to the first attribute included in the first metadata is missing, the first metadata The information processing according to any one of claims 1 to 3, wherein second metadata having a second attribute whose similarity with one attribute is equal to or greater than a threshold is extracted as the corresponding metadata. apparatus.   When the plurality of information sources have identifiers for using the same system, the search unit refers to a follow relationship indicating a relationship between identifiers corresponding to the plurality of information sources, and The information according to any one of claims 1 to 4, wherein the first metadata having the follow relationship is preferentially extracted as the corresponding metadata with respect to the information source that generated the data. Processing equipment.   The search unit refers to the follow relationship, and sets a higher importance level of the corresponding metadata transmitted from the information source as the number of people interested in the information source increases. The information processing apparatus according to claim 5.   The said collection part collects the positional information on this information source from the place name contained in the text created by this general user, when the said information source is a general user. The information processing apparatus according to any one of claims.   The information source is a fixed-point camera that is installed in a commercial facility or road and captures a moving image or a still image, a microphone that acquires an audio signal installed in an evacuation center, disaster information announced by a local government or mass media, and information on weather The information processing apparatus according to claim 1, further comprising at least one of disaster information transmitted from a general user. Collecting first metadata about the information that does not have a standardization common to the plurality of information sources from a plurality of information sources that transmit the information;
Storing a first attribute indicating an item of an element included in the first metadata and a first attribute value that is a value corresponding to the first attribute in the storage unit in association with each first metadata;
Based on the correspondence between the second attribute indicating the item of the element included in the newly acquired second metadata, the second attribute value corresponding to the second attribute, and the first attribute and the first attribute value An information processing method characterized by searching a plurality of the first metadata and extracting corresponding metadata that is the first metadata corresponding to the second metadata. Computer
Collecting means for collecting, from each of a plurality of information sources that transmit information, first metadata relating to the information that does not have a common standard among the plurality of information sources;
Storage means for storing a first attribute indicating an item of an element included in the first metadata and a first attribute value that is a value corresponding to the first attribute in association with each first metadata;
Based on the correspondence between the second attribute indicating the item of the element included in the newly acquired second metadata, the second attribute value corresponding to the second attribute, and the first attribute and the first attribute value An information processing program for causing a plurality of first metadata to be searched and functioning as search means for extracting corresponding metadata that is the first metadata corresponding to the second metadata.